Type II errors

• from: Scoring binary classification

• Alpha levels and beta levels are related:

  • type I error
    • rejecting the null hypothesis when it is true.
      • the incorrect rejection of a true null hypothesis
    • alpha level
      • the probability of a type I error (rejecting the null hypothesis when it is true)
  • type II error
    • accepting the null hypothesis when it’s false.
      • the incorrect conclusion that there is no statistical significance (if there was, you would have rejected the null).
      • you don’t reject a false null hypothesis.
    • beta level, usually just called beta(β)
      • the probability of a type II error (accepting the null hypothesis when it’s false)

Reference:

• Beta Level: Definition & Examples - Statistics How To
• Scoring binary classification